In the ever-competitive world of CRM Marketing, customer segmentation is one of the most powerful tools at a marketer’s disposal. By dividing your customer base into distinct groups, you can tailor your marketing messages and strategies to meet the unique needs and preferences of each segment. But when it comes to creating those segments, where should you start? Should you rely on the hard facts of customer data, or delve into the soft insights of qualitative research?
Both approaches have their merits, but each comes with its own strengths and challenges. In this blog, we’ll explore the benefits and drawbacks of starting your segmentation process with customer data versus qualitative research, helping you determine the best path for your relationship marketing strategy.
Starting with Customer Data: The Power of Numbers
When it comes to segmentation, customer data often takes centre stage. After all, we live in a data-driven world, and the ability to measure customer behaviour through analytics can offer powerful insights. By leveraging historical data, such as purchase patterns, web browsing behaviours, or social media engagement, businesses can group customers based on tangible, trackable metrics. Common data points for segmentation include:
• Demographic data: Age, gender, income, and location.
• Behavioural data: Purchase frequency, average order value, and website interactions.
• Engagement data: Email open rates, social media interactions, and customer service interactions.
Advantages of Using Data for Segmentation:
1. Accuracy and Objectivity: Customer data is factual and quantifiable, making it easier to segment based on hard evidence rather than assumptions. When you base segmentation on actual behaviour, you can be confident that the groups you create reflect real-world actions.
2. Scalability: Customer data, particularly when collected via digital touchpoints (website, email, social media), can be gathered and processed at scale. This makes it easier to apply segmentation to large groups of customers, which is essential for large businesses or brands with significant customer bases.
3. Real-Time Insights: With data-driven segmentation, businesses can analyse customer behaviour in real time, allowing for quick adjustments to campaigns and offers. For instance, if you notice a sudden shift in buying patterns, you can adapt your strategy to reflect this change.
4. Automation: Data-driven segmentation can be easily integrated into marketing automation tools, enabling personalised messaging to specific segments automatically. For example, a customer who makes frequent repeat purchases can be targeted with loyalty rewards, while a new customer might receive an introductory offer.
Challenges of Using Data for Segmentation:
1. Misses the “Why” Behind the Behaviour: While data is incredibly useful for understanding what customers do (e.g., how often they buy, how much they spend), it doesn’t always explain why they behave the way they do. Without this context, you may create segments that are too broad or miss key motivations behind customer actions.
2. Data Limitations: Data is only as good as what you collect. If you’re relying solely on transactional data or behavioural data from a single channel, you could miss out on a full understanding of your customer base. Additionally, some data might be skewed or incomplete, leading to inaccurate segmentation.
3. Over-Reliance on Historical Data: Relying on past behaviours to predict future actions can be problematic. Customer preferences and behaviour are fluid and can change quickly, especially in a fast-moving digital landscape. If your segmentation is purely based on historical data, you risk missing emerging trends or shifts in customer behaviour.
Starting with Qualitative Research: The Power of Insight
While customer data offers a wealth of quantitative insights, qualitative research provides a deeper understanding of customer motivations, preferences, and attitudes. This research often involves methods like focus groups, interviews, surveys, and social listening, all of which help you tap into the “why” behind customer behaviour. By talking directly to customers or observing their behaviour in context, you can gain valuable insights into their needs and pain points.
Advantages of Using Qualitative Research for Segmentation:
1. Deeper Insights into Customer Motivations: Qualitative research gives you the opportunity to understand why customers act in certain ways. This deeper understanding can help you create segments based not just on behaviours but also on attitudes, values, and needs. For example, a segment could be created based on customers who are environmentally conscious, even if they don’t make eco-friendly purchases as often.
2. Identification of New Segments: Qualitative research can uncover new and unexpected customer segments that data alone may miss. Through open-ended questions and discussions, customers may reveal underlying reasons for their behaviours, or unique pain points that hadn’t previously been considered. This is especially valuable when you’re trying to reach new audiences or explore niche markets.
3. Personal Connection: Qualitative research allows you to engage directly with your customers, building a deeper connection. This approach can yield insights into emotions and perceptions, which can be pivotal in crafting customer experiences that feel personalised and human.
4. Flexibility: Unlike data-driven segmentation, which is often confined to predefined categories, qualitative research allows for more flexibility in how you create segments. You can use the insights gained from customer interviews or focus groups to adjust your segmentation strategy as new patterns and trends emerge.
Challenges of Using Qualitative Research for Segmentation:
1. Subjectivity: One of the biggest drawbacks of qualitative research is that it’s inherently subjective. Insights are based on individual opinions, which can be influenced by a variety of factors, including the interviewer’s style or respondents’ biases. This makes it harder to quantify or generalise findings.
2. Limited Scalability: Qualitative research typically involves a smaller sample size compared to customer data. As such, it may not provide the same broad-level insights needed to scale segmentation efforts, especially for large businesses or organisations with large customer bases.
3. Time and Resource Intensive: Conducting qualitative research, such as focus groups or in-depth interviews, can be time-consuming and costly. It often requires skilled moderators, transcription services, and data analysis, which may not be feasible for every business, especially those with limited marketing budgets.
4. Difficult to Automate: Unlike data-driven segmentation, which can be automated and integrated into CRM systems, qualitative research requires human involvement. This makes it more difficult to integrate directly into ongoing marketing campaigns.
Combining Data and Qualitative Research: The Best of Both Worlds
Rather than choosing one approach over the other, the most effective segmentation strategy often combines the strengths of both data and qualitative research. By integrating quantitative insights with qualitative insights, you can create richer, more nuanced customer segments.
For example:
• Data-first approach: Start with data-driven segmentation to identify broad customer categories (e.g., frequent buyers, high spenders, or customers who only buy during sales).
• Qualitative refinement: Use qualitative research to dive deeper into the motivations and attitudes of these segments. You might find, for example, that your high-spending customers are motivated by convenience, while your frequent buyers are driven by loyalty to the brand.
• Ongoing feedback loop: As you continue collecting data on customer behaviour, use qualitative insights to periodically reassess and refine your segmentation strategy.
This hybrid approach helps you create more dynamic and responsive segmentation strategies that are grounded in both the “what” and the “why” of customer behaviour.
Conclusion: The Best Starting Point for Customer Segmentation
Ultimately, whether you start with customer data or qualitative research depends on your objectives, resources, and the scale of your business. For businesses with a large customer base or those looking for fast, scalable insights, data-driven segmentation offers a solid foundation. However, if you’re looking for deeper insights into customer attitudes, emotions, and values, qualitative research is invaluable.
The best practice for modern relationship marketing is to combine both methods. Data gives you the scale and speed, while qualitative research gives you the depth and nuance. Together, these two approaches will help you create customer segments that are more than just numbers—they’ll reflect the true motivations and desires of your audience, allowing you to create more personalised, relevant marketing campaigns that drive long-term loyalty.
